org.apache.commons.math.optimization.direct
Class SimplexOptimizer

java.lang.Object
  org.apache.commons.math.optimization.direct.BaseAbstractScalarOptimizer<MultivariateRealFunction>
      org.apache.commons.math.optimization.direct.SimplexOptimizer

All Implemented Interfaces:

BaseMultivariateRealOptimizer<MultivariateRealFunction>, BaseOptimizer<RealPointValuePair>, MultivariateRealOptimizer

public class SimplexOptimizer
extends BaseAbstractScalarOptimizer<MultivariateRealFunction>
implements MultivariateRealOptimizer

This class implements simplex-based direct search optimization.

Direct search methods only use objective function values, they do not need derivatives and don't either try to compute approximation of the derivatives. According to a 1996 paper by Margaret H. Wright (Direct Search Methods: Once Scorned, Now Respectable), they are used when either the computation of the derivative is impossible (noisy functions, unpredictable discontinuities) or difficult (complexity, computation cost). In the first cases, rather than an optimum, a not too bad point is desired. In the latter cases, an optimum is desired but cannot be reasonably found. In all cases direct search methods can be useful.

Simplex-based direct search methods are based on comparison of the objective function values at the vertices of a simplex (which is a set of n+1 points in dimension n) that is updated by the algorithms steps.

The setSimplex method must be called prior to calling the optimize method.

Each call to optimize will re-use the start configuration of the current simplex and move it such that its first vertex is at the provided start point of the optimization. If the optimize method is called to solve a different problem and the number of parameters change, the simplex must be re-initialized to one with the appropriate dimensions.

Convergence is checked by providing the worst points of previous and current simplex to the convergence checker, not the best ones.

Since:

3.0

Version:

$Id$

See Also:

AbstractSimplex

Field Summary

Fields inherited from class org.apache.commons.math.optimization.direct.BaseAbstractScalarOptimizer

evaluations

Constructor Summary

SimplexOptimizer()
Constructor using a default convergence checker.

SimplexOptimizer(ConvergenceChecker<RealPointValuePair> checker)

SimplexOptimizer(double rel, double abs)

Method Summary

protected RealPointValuePair	doOptimize() Perform the bulk of the optimization algorithm.
void	setSimplex(AbstractSimplex simplex) Set the simplex algorithm.

Methods inherited from class org.apache.commons.math.optimization.direct.BaseAbstractScalarOptimizer

computeObjectiveValue, getConvergenceChecker, getEvaluations, getGoalType, getMaxEvaluations, getStartPoint, optimize, setConvergenceChecker

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.commons.math.optimization.BaseMultivariateRealOptimizer

optimize

Methods inherited from interface org.apache.commons.math.optimization.BaseOptimizer

getConvergenceChecker, getEvaluations, getMaxEvaluations, setConvergenceChecker

Constructor Detail

SimplexOptimizer

public SimplexOptimizer()

Constructor using a default convergence checker.

SimplexOptimizer

public SimplexOptimizer(ConvergenceChecker<RealPointValuePair> checker)

Parameters:

checker - Convergence checker.

SimplexOptimizer

public SimplexOptimizer(double rel,
                        double abs)

Parameters:

rel - Relative threshold.

abs - Absolute threshold.

Method Detail

setSimplex

public void setSimplex(AbstractSimplex simplex)

Set the simplex algorithm.

Parameters:

simplex - Simplex.

doOptimize

protected RealPointValuePair doOptimize()

Perform the bulk of the optimization algorithm.

Specified by:

doOptimize in class BaseAbstractScalarOptimizer<MultivariateRealFunction>

Returns:

the point/value pair giving the optimal value for the objective function.